# Data Visualization A Practical Introduction Assignment | Homework Help Websites

Start by playing around with the `gapminder` data a little more. You can try each of these explorations with `geom_point()` and then with `geom_smooth()`, or both together.

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• What happens when you put the `geom_smooth()` function before `geom_point()` instead of after it? What does this tell you about how the plot is drawn? Think about how this might be useful when drawing plots.
• Change the mappings in the `aes()` function so that you plot Life Expectancy against population (`pop`) rather than per capita GDP. What does that look like? What does it tell you about the unit of observation in the dataset?
• Try some alternative scale mappings. Besides `scale_x_log10()` you can try `scale_x_sqrt()` and `scale_x_reverse()`. There are corresponding functions for y-axis transformations. Just write `y`instead of `x`. Experiment with them to see what sort of effect they have on the plot, and whether they make any sense to use.
• What happens if you map `color` to `year` instead of `continent`? Is the result what you expected? Think about what class of object `year` is. Remember you can get a quick look at the top of the data, which includes some shorthand information on the class of each variable, by typing `gapminder`.
• Instead of mapping `color = year`, what happens if you try `color = factor(year)`?

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